Spatial Divide and Conquer with Motion Cues for Tracking through Clutter
Zhaozheng Yin; Collins, R.
Computer Vision and Pattern Recognition, 2006 IEEE Computer Society Conference on
Volume 1, Issue , 17-22 June 2006 Page(s): 570 - 577
Digital Object Identifier 10.1109/CVPR.2006.286
Summary: Tracking can be considered a two-class classification problem between the foreground object and its surrounding background. Feature selection to better discriminate object from background is thus a critical step to ensure tracking robustness. In this paper, a spatial divide and conquer approach is used to subdivide foreground and background into smaller regions, with different features being selected to distinguish between different pairs of object and background regions. Temporal cues are incorporated into the process using foreground motion prediction and motion segmentation. Appearance weight maps tailored to each spatial region are merged and combined with the motion information to form a joint weight image suitable for mean-shift tracking. Examples are presented to illustrate that divide and conquer feature selection combined with motion cues handles spatial background clutter and camouflage well.
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